AIMC Topic: Neural Networks, Computer

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Application of Convolution Neural Network (CNN) Model Combined with Pyramid Algorithm in Aerobics Action Recognition.

Computational intelligence and neuroscience
In order to realize high-accuracy recognition of aerobics actions, a highly applicable deep learning model and faster data processing methods are required. Therefore, it is a major difficulty in the field of research on aerobics action recognition. B...

Gastrointestinal Tract Disease Classification from Wireless Endoscopy Images Using Pretrained Deep Learning Model.

Computational and mathematical methods in medicine
Wireless capsule endoscopy is a noninvasive wireless imaging technology that becomes increasingly popular in recent years. One of the major drawbacks of this technology is that it generates a large number of photos that must be analyzed by medical pe...

Construction of Community Life Service in the Sharing Economy Based on Deep Neural Network.

Computational intelligence and neuroscience
Currently, the development of sharing economy and interconnection also has a profound impact on community life services. This study is based on the deep neural network theory, combined with the evolution mechanism of the commercial network of the com...

Current uses, emerging applications, and clinical integration of artificial intelligence in neuroradiology.

Reviews in the neurosciences
Artificial intelligence (AI) is a branch of computer science with a variety of subfields and techniques, exploited to serve as a deductive tool that performs tasks originally requiring human cognition. AI tools and its subdomains are being incorporat...

Preoperative prediction of postoperative urinary retention in lumbar surgery: a comparison of regression to multilayer neural network.

Journal of neurosurgery. Spine
OBJECTIVE: Postoperative urinary retention (POUR) is a common complication after spine surgery and is associated with prolongation of hospital stay, increased hospital cost, increased rate of urinary tract infection, bladder overdistention, and auton...

Using synthetic data generation to train a cardiac motion tag tracking neural network.

Medical image analysis
A CNN based method for cardiac MRI tag tracking was developed and validated. A synthetic data simulator was created to generate large amounts of training data using natural images, a Bloch equation simulation, a broad range of tissue properties, and ...

Pre-surgical and Post-surgical Aortic Aneurysm Maximum Diameter Measurement: Full Automation by Artificial Intelligence.

European journal of vascular and endovascular surgery : the official journal of the European Society for Vascular Surgery
OBJECTIVE: The aim of this study was to evaluate an automatic, deep learning based method (Augmented Radiology for Vascular Aneurysm [ARVA]), to detect and assess maximum aortic diameter, providing cross sectional outer to outer aortic wall measureme...

CT slice alignment to whole-body reference geometry by convolutional neural network.

Physical and engineering sciences in medicine
Volumetric medical imaging lacks a standardised coordinate geometry which links image frame-of-reference to specific anatomical regions. This results in an inability to locate anatomy in medical images without visual assessment and precludes a variet...

Reducing variability of breast cancer subtype predictors by grounding deep learning models in prior knowledge.

Computers in biology and medicine
Deep learning neural networks have improved performance in many cancer informatics problems, including breast cancer subtype classification. However, many networks experience underspecificationwheremultiplecombinationsofparametersachievesimilarperfor...

Automated detection of bioimages using novel deep feature fusion algorithm and effective high-dimensional feature selection approach.

Computers in biology and medicine
The classification of bioimages plays an important role in several biological studies, such as subcellular localisation, phenotype identification and other types of histopathological examinations. The objective of the present study was to develop a c...